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This is a Quantitative Study study.

October 23, 2025OTC Brasil

Predicting Bottom-Hole Pressure in Wells Using Machine Learning: A Cost-Effective Solution for Missing Gauge Data

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Accurate bottom-hole pressure predictions enhance reservoir management and optimize production.
Artificial Neural Networks significantly outperform linear regression, achieving an R-squared of 97%.
Real-time monitoring approach utilizes existing data, reducing costs associated with gauge malfunctions.
Method's scalability indicates potential applications in injection wells and broader reservoir management.

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Analysis shows real-time monitoring improves bottom-hole pressure prediction in wells, suggesting a cost-effective workover alternative.

Sowek et al. (2025) studied this question.

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